The Chair of Intelligent Technical Design is concerned with the application of modern information and communication technology (ICT) during the design, the construction and the operation of civil infrastructure, such as buildings, bridges, tunnels, road and pipe networks. In this regard, we use methods of Building Information Modelling (BIM), Computer Vision and Machine Learning as well as Virtual and Augmented Reality to efficiently and sustainably inform decision makers.
"Intelligent Technical Design refers to a design approach that utilizes advanced technologies, such as artificial intelligence and machine learning, to optimize the design process and improve the performance, efficiency, and sustainability of building and infrastructure systems. It integrates data-driven insights, real-time performance monitoring, and machine learning algorithms into the design process to make informed decisions, automate manual processes, and reduce the risk of human error. The goal of Intelligent Technical Design is to create high-performing, sustainable, and efficient building and infrastructure systems." [ChatGPT, 2023]
Two papers presented at the 13th Linked Data in Architecture and Construction Workshop (LDAC2025)
Four members of the chair participated in this year's LDAC workshop and EC3 conference in Porto.
Judith Krischler and Sebastian Schilling (HTW) presented the results of a joint research project between the Bauhaus-Universität Weimar, the Dresden University of Applied Sciences (HTW) and the Technical University of Berlin (TUB) on behalf of their other co-authors Dr. Jakob Taraben, Dr. Maximilian Sternal (TUB), Prof. Christian Koch and Prof. Christian Clemen (HTW). The paper, entitled "A Standards-Based Approach on BIM-GIS-Integration: Extending the Multi-Model Container Schema", can be found here.
Paul-Christian Schuler presented the results of the mFUND project ‘openSIM’ on behalf of his co-authorsMahsa Mirboland, Yannic Stark (Marx Krontal Partner GmbH), Abdullah Al Mohammad (customQuake) andProf. Christian Koch. The article, entitled ‘Linked Data for Structural Diagnostics: A Semantic Framework for Sustainable Infrastructure Management,’ can be found here.
